State Departments of Transportation (DOTs) have made steady progress in the use of data and information systems to manage transportation assets. Advances in data acquisition, management, and reporting tools and technologies are enabling more automated, efficient, and integrated flows of data across systems and more agile and effective ways of delivering information needs to end users.
DOTs have strong incentives to take advantage of these advances; they face growing expectations from the public, increasing demand for transparency and accountability, and challenges to make best use of limited resources to deliver value.
This guidebook provides step-by-step techniques and a digital tool to:
- Assess current practice and establish a desired state.
- Identify and evaluate data- and information system-related improvements.
- Secure agency support for improvements and plan an implementation strategy.
The guidebook provides a structured approach that agencies can use to assess and advance current practices in use of data and information for TAM. This approach can be applied in a comprehensive fashion; it can be targeted for a particular asset; or it can focus on a particular topic area – such as data collection or data integration. The guidebook also provides supplemental resources that can help agencies with each step of the process – understanding the context for each of the assessment elements, learning about and evaluating possible improvements, and planning an implementation strategy.
Completing the full assessment process will result in 1) a shared understanding of current agency practice and a shared vision for how to advance, 2) a list of candidate data and information system improvements that could be used to close identified gaps; and 3) a prioritized list of improvements – created based on a systematic process of evaluating likely impact versus effort and agency implementation challenges.
The guidebook is structured around a data life-cycle framework. This life-cycle (illustrated in Figure 1-1) consists of five essential steps for making efficient and effective use of data and information for TAM. The data life-cycle approach was selected to reinforce the importance of anticipating how data will be used prior to collecting it. The data life-cycle can be viewed as a supply chain in which the finished product is a data-informed decision. Getting a quality product depends on sound practices for specifying data, collecting it, storing and integrating it and providing access to potential users, and having suitable analysis tools and processes in place.